Smile detection techniques aim to determine whether a static face image is smiling or not. The face image may be cropped from raw digital photos or videos using face detection methods.
Nowadays, many consumer electronic devices are equipped with cameras such as camera phones, digital signage, and even television. For such devices, smile detection may be employed in various applications. For instance, smile detection can be used in digital cameras/camera phones to automatically determine when the shutter may be closed. Also, smile detection can be used to conduct automatic surveys in digital signage/television applications. For instance, smile detection may be used to determine how many people enjoy particular programming, advertisements, etc.
In embedded applications, the computing and memory resources are usually very limited. Moreover, smile detection functionality may be required to be resident in memory for continuous execution (such as in digital signage). This makes power consumption an important factor. Unfortunately, existing smile detection approaches require considerable computing and memory resources. Moreover, some existing techniques on embedded devices are quite inaccurate.